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Open sourcing Restly – GPT-4 powered tutorials from your OpenAPI spec

Hacker News

Open sourcing Restly – GPT-4 powered tutorials from your OpenAPI spec

Hi HN - Marius (mbuleandra) and I built Restly as a side project. Restly generates a user-friendly tutorial against any OpenAPI spec. While building public-facing APIs, we found that writing these guides by hand took a lot of work. Many OpenAPI specs were too large to send to GPT-4 / Claude directly, and even when we could send them, we experienced lost-in-the-middle and hallucination issues. The project is very alpha but works against the Vocode API when we specify well-defined goals. Let us know your thoughts; we would love your contribution to the project! [1] https://getrestly.com/ [2] https://github.com/Get-Restly

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, user, code · Missing: mac, agents, macos
89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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